Chinese Control Conference (CCC)

Exploring Quantum Engineering from Resource Perspective

Tang Zenglin, Dai Hongyi, Ming Zhang

Published Jul 26, 2021• 1 citation

Abstract

From the viewpoint of engineering cybernetics, research paradigm shift may be necessary for investigating quantum systems and quantum artificial intelligence. When a quantum system or constructing a quantum information processing system is manipulated, one should not only consider what kind of resource is available, but also consider whether or not there is enough resource to support the control of quantum systems. Our recent researches can be regarded as exploring quantum engineering from resource perspective. We intend to propose and answer the following questions: what will happen when quantum measurements, quantum computation, quantum entangled states or quantum network are available for the public. In our opinion, performing quantum measurement, completing quantum computation, preparing quantum entangled states and building quantum network can be regarded as cost of resources. Hopefully we should shape a new research paradigm from the resource perspective.

DOI: 10.23919/ccc52363.2021.9549513

Related papers

Quantum Computing and AI: Perspectives on Advanced Automation in Science and Engineering

Tadashi Kadowaki

Recent advances in artificial intelligence (AI) and quantum computing are accelerating automation in scientific and engineering processes, fundamentally reshaping research methodologies. This perspective highlights parallels between scientific automation and established Computer-Aided Engineering (CAE) practices, introducing Quantum CAE as a framework that leverages quantum algorithms for simulation, optimization, and machine learning within engineering design. Practical implementations of Quantum CAE are illustrated through case studies for combinatorial optimization problems. Further discussions include advancements toward higher automation levels, highlighting the critical role of specialized AI agents proficient in quantum algorithm design. The integration of quantum computing with AI raises significant questions about the collaborative dynamics among human scientists and engineers, AI systems, and quantum computational resources, underscoring a transformative future for automated discovery and innovation.

arXiv:2505.10012May 15, 20250 citations

Quantum Computing in the Age of Artificial Intelligence: A Human-Centered Engineering Framework for Hybrid Intelligence

Vikrant Salar

This technical note presents a human-centered engineering framework for understanding quantum computing in the age of artificial intelligence. It argues that quantum computing should not be treated as magic, hype, or a universal replacement for classical computing, but as a disciplined computational model grounded in probability, linear algebra, measurement, physical systems, and resource constraints. The report connects quantum foundations with artificial intelligence, semiconductor systems, post-quantum security, scientific simulation, engineering education, and civilization-scale technology planning. It proposes a practical suitability framework for deciding when a quantum-AI approach is technically justified, resource-feasible, explainable, and socially useful. This report is a concise scholarly companion to the broader book project Quantum Computing in the Age of Artificial Intelligence: Engineering the Next Civilization by Vikrant Salar, Founder & Principal of SALAR Technologies LLC. It is intended for researchers, engineers, educators, technical founders, policy-minded readers, and reviewers interested in quantum computing, AI-assisted science, hybrid computing systems, post-quantum cryptography, and responsible technology development.

Jul 1, 20260 citations

Quantum artificial intelligence: A survey

Giovanni Acampora, Angela Chiatto, Roberto Schiattarella +1 more

Quantum computing and artificial intelligence are two highly topical fields of research that can benefit from each other’s discoveries by opening a completely new scenario in computation, that of quantum artificial intelligence. Indeed, on the one hand, artificial intelligence algorithms can be made computationally more efficient due to the potential speedup enabled by quantum phenomena; on the other hand, the complex development of quantum computing technologies and methodologies can be properly supported by the use of classical artificial intelligence approaches. The “entanglement” of these two disciplines is opening up completely new directions in computer science research, and this survey aims to provide a systematic and taxonomic overview of the work that has already been done and that which will begin in the near future.

Computer Science ReviewSep 10, 202514 citations

Quantum Cybernetics and Complex Quantum Systems Science: A Quantum Connectionist Exploration

Carlos Pedro Gonçalves

Quantum cybernetics and its connections to complex quantum systems science is addressed from the perspective of complex quantum computing systems. In this way, the notion of an autonomous quantum computing system is introduced in regards to quantum artificial intelligence, and applied to quantum artificial neural networks, considered as autonomous quantum computing systems, which leads to a quantum connectionist framework within quantum cybernetics for complex quantum computing systems. Several examples of quantum feedforward neural networks are addressed in regards to Boolean functions' computation, multilayer quantum computation dynamics, entanglement and quantum complementarity. The examples provide a framework for a reflection on the role of quantum artificial neural networks as a general framework for addressing complex quantum systems that perform network-based quantum computation, possible consequences are drawn regarding quantum technologies, as well as fundamental research in complex quantum systems science and quantum biology.

arXiv:1402.1141NeuroQuantologyJan 21, 20158 citations

Quantum Entanglement as a New Quantum Informational ProcessingResource

Jozef Gruska

Potential of quantum entanglement for quantum computation and quantum communication is explored and various approaches to measurement and transformations of quantum entanglement are analysed and compared.

Jan 1, 20020 citations

Quantum Entanglement-Based Distributed Reasoning Engine

Jincheng Zhang

This paper proposes a novel distributed reasoning engine leveraging the non-local property of quantum entanglement for enhanced information processing and logical operations. The core claim rests on utilizing entanglement to overcome the limitations of classical distributed systems, enabling long-distance, high-speed computation. The proposed mechanism involves encoding information into entangled states and performing logical operations through their interactions. Quantum control techniques are explored to optimize the manipulation and measurement of these entangled states. We demonstrate that this approach offers a fundamental shift in distributed computing, enabling true parallel computation and instantaneous information transfer, thereby transcending the physical constraints of classical systems. The engine's design focuses on modularity and scalability, aiming to provide a robust framework for complex reasoning tasks. Further research will concentrate on developing practical implementations and exploring the engine's applicability across diverse domains, including secure communication, advanced sensor networks, and artificial intelligence. ---

Aug 31, 20260 citations